2019-10-22
The ÅBU - Annual Bibliometric Monitoring - is sometimes perceived as a annual reporting event for ranking and evaluating research publications at KTH.
Amongst some researchers it can be perceived as an employee review tool… and it sounds from those who have done it, that it has not always been a pleasant experience to present the ÅBU to some stakeholders.
The Bibliometrics group has thought about how it could be developed further, in the future, to bring more value to the different stakeholders.
Existing indicators used at aggregate levels are not good at individual level (low n < 50). The Bibliometrics group want to use better indicators which are more suitable as indicators at the individual level.
Add more "altmetrics" for individual researchers for a broader view of their impact. "How can I track my own citations? In what countries are the publications made? Where should I publish?". Data sources: Altmetric (R package rAltmetric). Mendeley (R packages RMendeley).
Which countries and universities do researchers co-publish with? Who cites them? Data source: WoS documents. These have addresses which could be used to show which countries researchers have collaborated with.
Add more data related to Open Access publications. Data sources: DOAJ - Directory of Open Access Journals - provides free and open data and metadata of relevance for open access journal publications (data dumps are available). Unpaywall free and open API provides data. (R package roadoi can be used).
Some possibilities:
Ideas:
Who is Tuija Sonkkila, from Finland? She is working at Aalto University Leadership Support Services. Altmetrics, SQL, Power BI, QlikView, data wrangling. She has written a paper on Metrics, Altmetrics, Data Visualization
She has developed Shiny apps covering bibliometrics analytics for Aalto University. She also produces analytics and reporting on other things like staff mobility: https://github.com/tts/mobility2018
Tuijas web page and private blog at .
Here are some links to her open source work, based on R, often using Shiny:
A couple of visual examples follow, involving use of open source based tools and visualizations that are web-friendly and responsive and interactive.
We will show how usage of visualizations such as maps, open access data sources and other modern analytics tools could be used to develop the ÅBU report in the future (v 1.2+)